Wow, the Voyager data is certainly ress rewarding to work with than Cassini or Galileo. I didn't realize how much more sensitive CCDs really are than vidicons, there's noise all around, even in several-second exposures. Not to mention geometric distortions and smear. Some quick-n-dirty stuff:

Curiously, there's a subtle blockiness in the noise (as well as other regions, but most noticeable there) in this geometrically calibrated data that's very reminiscent of JPEG artifacts, which is interesting. The blockiness appears to be on a 8-pixel block basis too, at first glance at least. I'm wondering if there was a lossy compression step introduced in the calibration procedure somewhere.

Wow, the Voyager data is certainly ress rewarding to work with than Cassini or Galileo. I didn't realize how much more sensitive CCDs really are than vidicons, there's noise all around, even in several-second exposures. Not to mention geometric distortions and smear. Some quick-n-dirty stuff:

Curiously, there's a subtle blockiness in the noise (as well as other regions, but most noticeable there) in this geometrically calibrated data that's very reminiscent of JPEG artifacts, which is interesting. The blockiness appears to be on a 8-pixel block basis too, at first glance at least. I'm wondering if there was a lossy compression step introduced in the calibration procedure somewhere.

I have wondered about this too. I will say that there is more that can be coaxed out of the Dione and Hyperion images, though I used the raws, not the new calibrated versions. I haven't worked with the Titan set you posted.

Now if you've heard that from someone at the Rings Node, please ignore what follows. But if it's from looking at the background shading of some of the thumbnails published at the address above, I think that's an artifact of the processing img2png does.

Consider this. The NASA processing subtracts a calibration image, applies further corrections, and scales the pixel values so that value 10000 has the REFLECTANCE_SCALING_FACTOR given in the PDS label, and the values lie in the range -32768 to +32767.

Now the dark background pixels have values which cluster around zero, but sometimes there are a lot of negative ones, and sometimes very few negative values. img2png converts all negative values to zero, so if the slight shading that's there is mostly in the negative range it is lost, but if it's mostly just positive, the shading remains. The contrast adjustment that's applied before img2png creates a thumbnail then emphasizes any shading that remains in the image.

This is not to say that Bjorn did the wrong thing in picking zero. PNG cannot cope with negative values (nor can any other mainstream image type I've come across for that matter) so one has to do something with them. Adding 32768 isn't an option as that would make the images and the background too bright. Choosing a value depending on the image doesn't always work either as the darker limbs and interiors of the moons may have pixel values lower than the background shading values which you want to remove.

In other words, I don't have an answer to this yet.

I've also noticed that if there was a reseau mark on the edge of a moon's image, you can get a mid-gray disc apparently sticking out into empty space.

I did some systematic experimental work on partial calibration of Voyager 1 wide angle images, in part to better see the Titan wide angle approach sequence. I found that there were several sets of images with identical image parameters that therefore should have had identical patterns of dark current shading.. but had dramatically different dark current shading patterns. Averaging a number of dark images in a "real world" matching set and subtracting that from a matched data image gave essentially perfect dark image subtraction down to random noise levels in the data.

It helped that I could do that in floating point real number image processing, where I had absolutely no problem handling negative data numbers, but the important thing was finding out that there must be some missing image parameter that affects dark current.

The most distinctive things to evaluate dark current matches are the absolute values of dark current at the top AND bottom of the images in what should be black-space parts of images. Both absolute values of dark current and the top-to-bottom gradient varies with imaging parameters inclulding the unidentifiable one.

I noticed that on this page you have links to the Voyager camera calibration data. I discovered this a couple of years ago and made a spreadsheet to show how the different filters for each colour fit together. I used the *.TAB files at the Ring Node.

One thing you will notice is that the centre frequency and bandwidth of the filters are altered from their nominal values by the response of the optical path and the vidicon tube.

Another thing to notice is that the response of the orange filter is completely contained within the green filter. So if you were composing a colour composite image using the green and orange pixel values, you would be counting the orange values twice, hence the green minus orange curve. Some double accounting also occurs between green and blue and between blue and violet, but the correction is less obvious.

All this and more is in my spreadsheet. I made it using Gnumeric as Excel wouldn't quite do what I wanted.(Mmm, UMSF doesn't like Gnumeric spreadsheets for some reason, and the .xml version doesn't look right.)What you're missing is an approximation to how the human eye would see each filter colour, the RGB ratio for each filter and the area under each curve in the graphs above. These should help in constructing colour images from either the raw data with an appropriate calibration image subtracted, or from the calibrated or geometrically corrected images published by the Ring Node. Some scaling of pixel values is needed to correct for different exposure times, filter response (area under curve) and to avoid saturation.

...The most distinctive things to evaluate dark current matches are the absolute values of dark current at the top AND bottom of the images in what should be black-space parts of images. Both absolute values of dark current and the top-to-bottom gradient varies with imaging parameters inclulding the unidentifiable one.

Thanks Ed. I had noticed how the dark current varies between images and that you have to pick your calibration images carefully to match. The Ring Node mentions this too in the notes about the Saturn and Uranus calibration projects. I see that the corrected Saturn images have passed peer review now.

Another suggestion I read once for removing gross distortions was to chop 10 pixels off each image edge, and to round the corners off at a radius of 480 pixels from the centre.

Now if you've heard that from someone at the Rings Node, please ignore what follows. But if it's from looking at the background shading of some of the thumbnails published at the address above, I think that's an artifact of the processing img2png does.

I did in fact hear this from the rings node:

QUOTE

Also please be aware that you have obtained volumes that are still in peer review status. A final version of the data set is in progress but will probably not be delivered for several months. In the mean time, our peer review panel did identify problems with some of the images---apparently, they were processed with inappropriate background models and so are not as photometrically accurate as they should be. We built a highly automated procedure to process the images, and apparently it was not fool-proof. You can read more about the reviews at http://pds-rings.seti.org/reviews/.

This means two things. First, be a little bit skeptical about any images that appear strange. Second, please report any errors that you find to us so that we can be sure that they are fixed in the final product.

Lien: The PDS Rings Node will review the images identified as having bad dark currents and the dark current files used, the dark current subtraction process, and will examine other calibrated files in an attempt to identify the cause of the problem. Once the extent and nature of the problem is identified, the Rings Node will modify the processing to correct all affected files. The results of this process will be transmitted to the panel members.

There's more on this issue in the various review documents there. I'm not sure which images have bad dark current subtraction.

Thanks for that link to the reviews webpage Emily, not easy to find otherwise.

I see in the report:Voyager Calibration Report should be included.Danielson et al. was published in JGR which, last we've heard, NEVER provides permission to distribute digital copies of their articles.

I would love to see this report, and I suspect so would many others, but after extensive searching I've never found a copy on-line. The Journal of Geophysical Research digital archives only go back to 1994 so even that route is closed to those like me who would otherwise have access.

Wow, the Voyager data is certainly ress rewarding to work with than Cassini or Galileo. I didn't realize how much more sensitive CCDs really are than vidicons, there's noise all around, even in several-second exposures. Not to mention geometric distortions and smear.

Two things I wanted to add. First, a lot of the smear is not due to vidicon. It is due to the lack of reaction wheels and the fact that some exposures were taken with the scan platform still in motion. Also, a lot of the junk in Voyager images is due to after-image effects in the vidicons which can be compensated for. Voyager (and Viking) had lamps that would white-out the camera, making the after-image an image of a solid white frame. This prevented after images of actual celestial objects, as plagued Mariner-9 and earlier probes. However, it also means that there is a lot more background junk in Voyager images. I have found that the so called "calibrated and geometrically corrected" frames have features that appear muted and without definition. However, when I remove the noise myself, I can get a sharper result. I say this to say that there are nice, clean images hiding under a lot of the Voyager frames. For Saturn, granted, Cassini supersedes this imagery, but for Jupiter (thanks to Galileo's limited coverage), Uranus, and Neptune, pulling whatever can be pulled from these images is quite rewarding. For instance, to use a Saturnian example, here is the best view of Enceladus from Voyager from the true raw frames.

That's a really nice Enceladus image. Very Cassini-like and to an untrained eye probably could be labeled as such. I'm beggining to find a new appreciation for high quality Voyager image products such as this, seeing how ungrateful the original raw data really is.

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